Synthetic aperture radar (SAR) has been adopted in this study to compensate for the shortage of obtaining structural information below the meadow covering. Structural information is obtained through field surveying and special remote sensing images. Influenced by weathering and meadow covering, the structural information in the meadow covering environment acquired through these methods is limited. Given its long wavelength, SAR has the advantage of penetrability, which can help in detecting structural information below the meadow covering. The technology can efficiently compensate for the disadvantage of spatial remote sensing and field observing in meadow covering area. This study aims (1) to establish a new method of structural interpretation in meadow covering based on GaoFen (GF)-3 Pol-SAR images; (2) to verify the application of GF-3 Pol-SAR images in four different atmosphere districts, namely, Gerze in Tibet, Nyingchi in Tibet, Qianjiadian in Beijing, and Sinan County in Guizhou Province; and (3) to interpret the faults and circular structures systematically in these areas and verify the authenticity and accuracy of interpretation through GF-3 SAR images by comparing with the 1∶50000 field mapping. GF-3 C-band SAR images have been used in detecting geology structures in this study because of its penetrability. GF-3 SAR images have the most observing modes worldwide. GF-3 full polarization mode images are utilized in this study to optimize the use of information in different polarization modes. To use the GF-3 SAR images effectively and accurately, the data processing procedure, including focusing, multi-looking, filtering, and geocoding, has been completed. The effect from speckle in the images can be effectively reduced by Lee filtering. Geocoding can ensure the accuracy of spatial information. The 90 m SRTM DEM data are obtained in the geocoding process to eliminate the topographic influence, which helps in optimizing the use of micro-topographic features to interpretation structures. On the contrary, the structures have different features in various polarization images. To optimize the use of features in different polarization images, the R-G-B combination of various polarization directions is used in the study. As the cross polarization has more peak features than the straight polarization, the cross polarization images have been merged as R channel and the straight polarization images have been merged as G and B channels. The interpretation capability of GF-3 SAR images has been increased by combining different polarization images. In this work, four study areas in different covering environments have been selected. The interpretation keys of faults and circular structures in study areas can be established on the basis of the combination of different polarization images, by analyzing the unique color, topography, and hydrographic features of faults and circular structures. The structural features have been systematically interpreted on the basis of the interpretation keys in four study areas. To analyze the authenticity and accuracy of interpretation through GF-3 SAR images, the structural features have been compared with the faults in 1∶50000 mapping. The color combination of different polarization images in four study areas has been acquired through data processing. Interpretation keys of faults and circular structures in study areas have been established by analyzing the unique color, topography, and hydrographic features of faults and circular structures. The structures in study areas have been interpreted systematically. Structural feature maps interpreted through GF-3 SAR images in study areas have been drawn. The faults in 1∶50000 field maps are contained in the structures interpreted through GF-3 SAR images, compared with 1∶50000 field mapping. The position of faults in 1∶50000 mapping fits the position of faults interpreted through GF-3 SAR images. The number of faults interpreted through GF-3 SAR images is largely increased. In this study, SAR has been adopted to detect geology structures. GF-3 SAR images have been used in four study areas, namely, Gerze in Tibet, Nyingchi in Tibet, Qianjiadian in Beijing, and Sinan County in Guizhou Province. By investigating structural interpretation through GF-3 SAR images in study areas, the following conclusions can be obtained: (1) A new method of structural interpretation in meadow covering based on GF-3 Pol-SAR images has been established. (2) The interpretation keys of faults and circular structures in four study areas, namely, Gerze in Tibet, Nyingchi in Tibet, Qianjiadian in Beijing, and Sinan County in Guizhou Province, based on GF-3 SAR images have been established. (3) The faults and circular structures in study areas have been interpreted systematically through GF-3 SAR images. The faults in 1∶50000 map have been contained in structural features interpreted through GF-3 SAR images, compared with 1∶50000 field mapping. The number of faults interpreted through GF-3 SAR images is largely increased. These increased faults are mostly structures below the meadow covering that cannot be observed through field work and special remote sensing images. The structural interpretation in four study areas demonstrates its authenticity and accuracy through GF-3 SAR images. The method based on GF-3 SAR images can effectively compensate for the disadvantage of field work and spatial remote sensing in meadow covering.

GF-3;Pol-SAR;meadow covering;structure interpretation;Loop structure